e7d58577095d95ee014e32c298ea0d53572ff56c,pyramid/arima/arima.py,ARIMA,fit,#ARIMA#Any#Any#,202

Before Change

        scoring = get_callable(self.scoring, VALID_SCORING)

        // don"t allow negative, don"t allow > n_samples
        cv = max(min(cv, n_samples), 0)

        def _fit_wrapper():
            // these might change depending on which one

After Change

        cv = max(cv, 0)

        // if cv is too big, raise
        if cv >= n_samples:
            raise ValueError("out-of-sample size must be less than number "
                             "of samples!")

        // If we want to get a score on the out-of-sample, we need to trim
        // down the size of our y vec for fitting. Addressed due to Issue /ቸ
        cv_samples = None
        cv_exog = None
        if cv:
            cv_samples = y[-cv:]
            y = y[:-cv]

            // This also means we have to address the exogenous matrix
            if exogenous is not None:
                cv_exog = exogenous[-cv:, :]
                exogenous = exogenous[:-cv, :]

        // This wrapper is used for fitting either an ARIMA or a SARIMAX
        def _fit_wrapper():
            // these might change depending on which one
            method = self.method

Instances